One Atmosphere: Integrating Air Pollution and Climate Policy and Governance

Few challenges pose a greater threat to a healthy planet and people than air pollution and climate change. Over the past three decades, research has demonstrated that integrated solutions to air pollution and climate change can yield co-benefits that support cost-effective, coherent policies. However, research on co-benefits has yet to generate policy responses consistent with this promise. This paper argues that realizing this potential requires more rigorous research on how governance affects the opportunities and incentives to align the interests of government agencies, scientists, and other stakeholders at multiple levels. The article proposes a “One Atmosphere approach” consisting of three building blocks to strengthen that alignment: (1) continually incorporating and strategically timing the introduction of integrated visions; (2) reforming governance arrangements to encourage interagency collaboration and multi-stakeholder cooperation; and (3) supporting integrated visions and institutional cooperation with standardized metrics and assessment methods. This article is also the introduction to the Special Issue ‘One Atmosphere: Integrating Air Pollution and Climate Policy and Governance’, aimed at fostering the multidisciplinary dialogue needed for more integrated air pollution and climate change policies.

An eCoach-Pain for Patients with Chronic Musculoskeletal Pain in Interdisciplinary Primary Care: A Feasibility Study

eHealth could support cost-effective interdisciplinary primary care for patients with chronic musculoskeletal pain. This study aims to explore the feasibility of the eCoach-Pain, comprising a tool measuring pain complexity, diaries, pain education sessions, monitoring options, and chat function. Feasibility was evaluated (June–December 2020) by assessing learnability, usability, desirability, adherence to the application, and experiences from patients and general practitioners, practice nurses mental health, and physiotherapists. Six primary healthcare professionals (PHCPs) from two settings participated in the study and recruited 29 patients (72% female, median age 50.0 years (IQR = 24.0)). PHCPs participated in a focus group. Patient data was collected by evaluation questionnaires, individual interviews, and eCoach-Pain-use registration. Patients used the eCoach during the entire treatment phase (on average 107.0 days (IQR = 46.0); 23 patients completed the pain complexity tool and used the educational sessions, and 12 patients the chat function. Patients were satisfied with the eCoach-Pain (median grade 7.0 (IQR = 2.8) on a 0–10 scale) and made some recommendations for better fit with patient-specific complaints. According to PHCPs, the eCoach-Pain is of added value to their treatment, and patients also see treatment benefits. However, the implementation strategy is important for successful use of the eCoach-Pain. It is recommended to improve this strategy and involve a case-manager per patient.

Development of Test Automation Framework for Printed Circuit Board Assembly

A Test Automation Framework is a bunch of rules or coding guidelines for test-process handling that is followed during coding. These are simple strategies that produce helpful results such as improved code re-usability, higher portability, diminished script support cost, reduced interdependency, higher interchangeability, and so on. This paper presents the development of a test automation framework for Printed Circuit Board Assembly (PCBA) to test the functionality and fault identification of the electronic circuit in the PCBA. It provides an integrated array of test and measurement Instruments which is automated using SCPI (Standard Command for programming Instrument) based commands to control test and measurement processes, making it simpler to configure and query. These test instruments imitate the environment in which the PCBA is to be deployed, which helps to observe its characteristics to determine whether it meets the expectation for which it was designed. Any possible variations in its characteristics due to fault are observed during testing and those faults are identified automatically using the data-driven fault analysis method.

Feasibility of Utilizing Social Media to Promote HPV Self-Collected Sampling among Medically Underserved Women in a Rural Southern City in the United States (U.S.)

Background: Social media (Facebook, WhatsApp, Instagram, Twitter) as communication channels have great potential to deliver Human papillomavirus self-test (HPVST) intervention to medically underserved women (MUW) such as women of low income. However, little is known about MUW’s willingness to participate in HPVST intervention delivered through social media. We evaluated factors that contribute to MUW’s intention to participate in the social media-related intervention for HPVST. Methods: A 21-item survey was administered among women receiving food from a local food pantry in a U.S. southern state. Independent variables were social media usage facilitators (including confidentiality, social support, cost, and convenience), and barriers (including misinformation, time-consuming, inefficient, and privacy concerns). Dependent variables included the likelihood of participating in social-driven intervention for HPVST. Both variables were measured on a 5-point scale. We used multinomial logistic regression to analyze the data. Results: A total of 254 women (mean age 48.9 ± 10.7 years) comprising Whites (40%), Hispanics (29%), Blacks (27%), and Other (4%) participated in the study. We found that over 44% of the women were overdue for their pap smears for the past three years, 12% had never had a pap smear, and 34% were not sure if they had had a pap smear. Over 82% reported frequent social media (e.g., Facebook) usage, and 52% reported willingness to participate in social media-driven intervention for HPVST. Women who reported that social media provide privacy (Adjusted Odds Ratio (AOR) = 6.23, 95% CI: 3.56, 10.92), provide social support (AOR = 7.18, 95% CI: 4.03, 12.80), are less costly (AOR = 6.71, 95% CI: 3.80, 11.85), and are convenient (AOR = 6.17, 95% CI: 3.49, 10.92) had significantly increased odds of participating in social media intervention for HPVST. Conclusions: The findings underscore that the majority of the MUW are overdue for cervical cancer screening, regularly use social media, and are willing to participate in social media-driven intervention. Social media could be used to promote HPV self-testing among MUW.

Perceptions, Vulnerability and Adaptation Strategies for Mitigating Climate Change Effects among Small Livestock Herders in Punjab, Pakistan

Pakistan is an agrarian nation that is among the most vulnerable countries to climatic variations. Around 20% of its GDP is produced by agriculture, and livestock-related production contributes more than half of this value. However, few empirical studies have been conducted to determine the vulnerability and knowledge of livestock herders, and particularly the smaller herders. Comprehending individual perceptions of and vulnerabilities to climate change (CC) will enable effective formulation of CC mitigation strategies. This study intended to explore individual perceptions of and vulnerabilities to CC based on a primary dataset of 405 small livestock herders from three agro-ecological zones of Punjab. The results showed that livestock herders’ perceptions about temperature and rainfall variations/patterns coincide with the meteorological information of the study locations. The vulnerability indicators show that Dera Ghazi Khan district is more vulnerable than the other two zones because of high exposure and sensitivity to CC, and lower adaptive capacity. However, all zones experience regular livelihood risks due to livestock diseases and deaths resulting from extreme climatic conditions, lower economic status, and constrained institutional and human resource capabilities, thus leading to increased vulnerability. The results indicate that low-cost local approaches are needed, such as provision of improved veterinary services, increased availability of basic equipment, small-scale infrastructure projects, and reinforcement of informal social safety nets. These measures would support cost-effective and sustainable decisions to enable subsistence livestock herders to adopt climate smart practices.

Digital Twins Supporting Efficient Digital Industrial Transformation

Industry 4.0 applications help digital industrial transformation to be achieved through smart, data-driven solutions that improve production efficiency, product consistency, preventive maintenance, and the logistics of industrial applications and related supply chains. To enable and accelerate digital industrial transformation, it is vital to support cost-efficient Industry 4.0 application development. However, the development of such Industry 4.0 applications is currently expensive due to the limitations of existing IoT platforms in representing complex industrial machines, the support of only production line-based application testing, and the lack of cost models for application cost/benefit analysis. In this paper, we propose the use of Cyber Twins (CTs), an extension of Digital Twins, to support cost-efficient Industry 4.0 application development. CTs provide semantic descriptions of the machines they represent and incorporate machine simulators that enable application testing without any production line risk and cost. This paper focuses on CT-based Industry 4.0 application development and the related cost models. Via a case study of a CT-based Industry 4.0 application from the dairy industry, the paper shows that CT-based Industry 4.0 applications can be developed with approximately 60% of the cost of IoT platform-based application development.

Video-Like Lossless Compression of Data Cube for Big Data Query in Wireless Sensor Networks

Wireless Sensor Networks (WSNs) contain many sensor nodes which are placed in chosen spatial area to temporally monitor the environmental changes. As the sensor data is big, it should be well organized and stored in cloud servers to support efficient data query. In this paper, we first adopt the streamed sensor data as "data cubes" to enhance data compression by video-like lossless compression (VLLC). With layered tree structure of WSNs, compression can be done on the aggregation nodes of edge computing. Then, an algorithm is designed to well organize and store these VLLC data cubes into cloud servers to support cost-effect big data query with parallel processing. Our experiments are tested by real-world sensor data. Results show that our method can save 94% construction time and 79% storage space to achieve the same retrieval time in data query when compared with a well-known database MySQL

Measuring post-discharge socioeconomic and quality of life outcomes in trauma patients: a scoping review

Purpose Trauma is a global public health challenge. Measuring post-discharge socioeconomic and quality-of-life outcomes can help better understand and reduce the consequences of trauma. Methods We performed a scoping review to map the existing research on post-discharge outcomes for trauma patients, irrespective of the country or setting in which the study was performed. The scoping review was conducted by searching six databases – MEDLINE, EMBASE, the Cochrane Library, Global Index Medicus, BASE, and Web of Science – to identify all articles that report post-discharge socioeconomic or quality of life outcomes in trauma patients from 2009 to 2018. Results Seven hundred fifty-eight articles were included in this study, extracting 958 outcomes. Most studies (82%) were from high-income countries (HICs). More studies from low- and middle-income countries (LMICs) were cross-sectional (71%) compared with HIC settings (46%). There was a wide variety of different definitions, interpretations, and measurements used by various articles for similar outcomes. Quality of life, return to work, social support, cost, and participation were the main outcomes studied in post-discharge trauma patients. Conclusions The wide range of outcomes and outcome measures reported across different types of injuries and settings. This variability can be a barrier when comparing across different types of injuries and settings. Post-discharge trauma studies should move towards building evidence based on standardized measurement of outcomes.